On Logistic Regression Approach to Survival Data and Power Divergence Statistics for Life Tables

Efron (1988) proposes the use of standard logistic regression techniques to estimate hazard rates and survival curves from survival data. These techniques allow statisticians to use parametric regression modeling on survival data in a flexible way that provides both estimates and standard errors. In the first part of this thesis, large sample properties of this logistic regression method are developed. It is shown that under some regularity conditions the hazard rate and survival function estimators are consistent and their corresponding asymptotic normality results also hold. Extension of Efron's method to regression model is proposed and their asymptotic properties again are examined.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Statistics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Lai, Kunjung

Contributors dc:contributor

• Ying, Ziliang

• Statistics

Identifier

(UMI)AAI9329089

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/72583